单变量绘图选择

I plot the distribution of every single variable and facet by quality.

The distribution of the quality

We can see the in the data set, high quality and the low quality wine is much less. The data tends to be normally distributed.

Fixed Acidity

The fixed acidity is most acids involved with wine or fixed or nonvolatile (do not evaporate readily), which is the skeleton of wine. The fixed acidity is concentrated in [6,10], and has a peak around 7. It can be considered as a normal distribution and the facet didn’t see much differences.

Volatile Acidity

Volatile acidity is the amount of acetic acid in wine, which at too high of levels can lead to an unpleasant, vinegar taste. The volatile acidity is concentrated in [0.1,1.0], and has a peak around 0.5. It shows high quality wine has a lower peak. When the quality equals to 5 and 6, the count peak is larger than 0.4, but when the quality equals to 7, the peak is less than 0.4. This might be an evident single facotr related to the wine quality, we need to explore more.

Volatile Acidit Ratio

Because the volatile acidity is evidently corresponded to the quality of wine, I want to explore more. When I search on the Internet, I found the balance of the taste is an important factor judging the quality of wine. So I was wondering the balance between acid smell and acid taste may influence the quality, so I create a new factor of volatile acidity ratio to measure the acid balance and plot the factor. But disappointedly, the new facotr didn’t work out. The distribution of volatile acidity is similiar to volatile acidity, even worse. The reason may be that volatile acidity is an unpleasent factor but the fixed acidity isn’t. People refresh the wine before drink at which the volatile acidity evaporates, so the balance between acid smell and acid taste cannot be moduled just by these two factor.

Citric Acid

Citric acid is found in small quantities, citric acid can add ‘freshness’ and flavor to wines. It seems like more high quality wine has more citric acid.

Residual Sugar

Residual sugar is the amount of sugar remaining after fermentation stops, it’s rare to find wines with less than 1 gram/liter and wines with greater than 45 grams/liter are considered sweet. The distribution shows that most of the wine in the data set is dry or semi-dry, and a very small amount of the sample are semi-sweet.

Chlorides

Chlorides is the amount of salt in the wine, it contains Chlorine. The distribution of chlorides didn’t show much difference in the facet. And I did an log-transform but it didn’t work either. The Chlorides itself is odorless, but under microbial action, it will transfer to Trichloroanisole(TCA). If the TCA is too much, the wine will have unpleasant smell like moldy old newspaper and wet cardboard. So I want to explore more about this factor next.

Free Sulfur Dioxide

Free sulfur dioxide is the free form of SO2 exists in equilibrium between molecular SO2 (as a dissolved gas) and bisulfite ion; it prevents microbial growth and the oxidation of wine. In low concentrations, SO2 is mostly undetectable in wine, but at free SO2 concentrations over 50 ppm, SO2 becomes evident in the nose and taste of wineToo much SO2 will make the wine smell like rotten eggs. The distribution didn’t show its direct impact on the quality, so I want to explore it combining other factors next.

Total Sulfur Dioxide

Total sulfur dioxide is amount of free and bound forms of S02. Most of the wine in the data set have total sulfur dioxide less than 0.1g/dm^3.

Density

The density of wine is close to that of water depending on the percent alcohol and sugar content. Density itself didn’t show strong correlation to quality, but people always say good wine have a ‘mellow’ taste, I will explore it combining the alcohol degree next.

pH

PH describes how acidic or basic a wine is on a scale from 0 (very acidic) to 14 (very basic); most wines are between 3-4 on the pH scale. It is relevent to acidity, and itself didn’t show strong correlation to quality. So I tend to give this factor up, and explore the acidity instead.

Sulphates

Sulphates is a wine additive which can contribute to sulfur dioxide gas (S02) levels, wich acts as an antimicrobial and antioxidant. The distribution doesn’t show much difference between different quality of wine. Because of its relevence to the SO2 level and antimicro, it is worth exploring.

Alcohol

Alcohol is the percent alcohol content of the wine. It affects not only density but also growing of microbe. It can be seen that good quality wine seems tend to be high alcohol content.

单变量分析

Summary the data set

##  fixed.acidity   volatile.acidity  citric.acid    residual.sugar  
##  Min.   : 4.60   Min.   :0.1200   Min.   :0.000   Min.   : 0.900  
##  1st Qu.: 7.10   1st Qu.:0.3900   1st Qu.:0.090   1st Qu.: 1.900  
##  Median : 7.90   Median :0.5200   Median :0.260   Median : 2.200  
##  Mean   : 8.32   Mean   :0.5278   Mean   :0.271   Mean   : 2.539  
##  3rd Qu.: 9.20   3rd Qu.:0.6400   3rd Qu.:0.420   3rd Qu.: 2.600  
##  Max.   :15.90   Max.   :1.5800   Max.   :1.000   Max.   :15.500  
##    chlorides       free.sulfur.dioxide total.sulfur.dioxide
##  Min.   :0.01200   Min.   :0.00100     Min.   :0.00600     
##  1st Qu.:0.07000   1st Qu.:0.00700     1st Qu.:0.02200     
##  Median :0.07900   Median :0.01400     Median :0.03800     
##  Mean   :0.08747   Mean   :0.01587     Mean   :0.04647     
##  3rd Qu.:0.09000   3rd Qu.:0.02100     3rd Qu.:0.06200     
##  Max.   :0.61100   Max.   :0.07200     Max.   :0.28900     
##     density             pH          sulphates         alcohol     
##  Min.   : 990.1   Min.   :2.740   Min.   :0.3300   Min.   : 8.40  
##  1st Qu.: 995.6   1st Qu.:3.210   1st Qu.:0.5500   1st Qu.: 9.50  
##  Median : 996.8   Median :3.310   Median :0.6200   Median :10.20  
##  Mean   : 996.7   Mean   :3.311   Mean   :0.6581   Mean   :10.42  
##  3rd Qu.: 997.8   3rd Qu.:3.400   3rd Qu.:0.7300   3rd Qu.:11.10  
##  Max.   :1003.7   Max.   :4.010   Max.   :2.0000   Max.   :14.90  
##     quality      total.acidity    volatile.acidity.ratio
##  Min.   :3.000   Min.   : 4.750   Min.   :0.01283       
##  1st Qu.:5.000   1st Qu.: 7.240   1st Qu.:0.04208       
##  Median :6.000   Median : 8.170   Median :0.06372       
##  Mean   :5.636   Mean   : 8.591   Mean   :0.06543       
##  3rd Qu.:6.000   3rd Qu.: 9.560   3rd Qu.:0.08465       
##  Max.   :8.000   Max.   :16.550   Max.   :0.20789

## [1] 1599   14

你的数据集结构是什么？

redwine数据集由一维因子变量（红酒序号）、红酒的11种特性以及红酒的质量评分组成，一共13维，且有1599条数据。

你的数据集内感兴趣的主要特性有哪些？

The main factor I interested in is volatile acidity which has direct impact on quality.

你认为数据集内哪些其他特征可以帮助你探索兴趣特点？

I want to explore the data from following aspect: - Influence of SO2 : using free.sulfur.dioxide, total.sulfur.dioxide and sulphate. - Relationship between acid and sugar : using fixed.acidity, citric.acid and residual.sugar. - Relationship between chlorides and antimicrobial environment : using chlorides, residual.sugar, alcohol and sulphates(the last 3 factors are relevent to micro growing).

根据数据集内已有变量，你是否创建了任何新变量？

total.acidity <- fixed.acidity + volatile.acidity
volatile.acidity.ratio <- volatile.acidity / total.acidity But the new factor is not good for distinguish the quality of wine, so I won’t focus on that.

在已经探究的特性中，是否存在任何异常分布？你是否对数据进行一些操作，如清洁、调整或改变数据的形式？如果是，你为什么会这样做？

Didn’t found abnormal distribution.
I have transfer the unit of free.sulfer.dioxide and total.sulfer.dioxide from mg/dm^3 to g/dm^3. And change the unit of density from g/cm^3 to g/dm^3 to match other factors.

双变量绘图选择

Using the ggpair to explore the relationship between 2 factors.

Try to find the strong single factor affect the quality of wine.

I try to find the relationship between quality and single factor. Actually it is little bit difficult because most of the factors are not strongly correlate to the quality. Here I display top3 factors that I think is most useful and rational.

1. Volatile acidity

We can see volatile acidity is negative to quality. But the best wine doesn’t have lowest volatile acidity. I guess there are 2 reasons: - The dataset of best quality wine are so small that causes the deviation. - The volatile acidity is not the only reason to judge the wine, so if the wine is excellent at other aspect but has acceptable high level volatile acidity, it still can be consider as high quality.

2. Citric acid

High quality wine has higher level of citric acid. Citric acid can add freshness and flavor in wine, which make the taste become rich.

3. Alcohol

High quality wine has higher level of alcohol. This may have following reasons: 1. High level of alcohol can protect the wine from microoraganism. 2. Wine which has high level of alcohol is more possible to be a good old wine.

双变量分析

探讨你在这部分探究中观察到的一些关系。这些感兴趣的特性与数据集内其他特性有什么区别？

Volatile acidity is negative to quality.
Citric acid is positive to quality.
Alcohol is positive to quality. These factors that I intereted in has stronger relevence to quality than others.

你是否观察到主要特性与其他特性之间的有趣关系？

Acid is relevent to pH.
Alcohol is relevent to density.
Density is relevent to acid.
Free.sulfur.dioxide is relevent to total.sulfur.dioxide. ### 你发现最强的关系是什么？
The linear relationship between pH and fixed.acidity.

多变量绘图选择

I explore the data from the following 4 aspect: - Influence of SO2 : using free.sulfur.dioxide, total.sulfur.dioxide and sulphate. - Relationship between acid and sugar : using fixed.acidity, citric.acid and residual.sugar. - Relationship between chlorides and antimicrobial environment : using chlorides, residual.sugar, alcohol and sulphates(the last 3 factors are relevent to micro growing). - Other organic matter: Using density and alcohol to explore the other organic matter in the wine.

1.Influence of SO2

We know that too much SO2 smell like rotten eggs, but too less SO2 will cause micro-polution. So in some degree, SO2 is indispensable. But what the difference between good and bad quality wine in this aspect? To explore this issue, I create 2 new factors:

SO2 ratio so2.ratio = free.sulfur.dioxide / Total Volatile Organic Compound = free.sulfur.dioxide / (free.sulfur.dioxide + volatile.acidity) SO2 ratio can measure the obvious degree of SO2.
SO2 control The sulphates control the so3+ in the wine, which can transform to so2. This factor can be consider as the release amount of SO2 when freshing the wine before taste. so2.control = (total.sulfur.dioxide - free.sulfur.dioxide) / sulphates

The plot shows us good wine have higher SO2 ratio and the slope of SO2 ratio and SO2 control is much large. The slope means the release rate SO2 when refreshing. From the plot, we can tell: - Good wine has higher SO2 ratio which can protect the wine from micro-polution better. - Good wine has higher SO2 releasing rate, which can much quickly make SO2 reach to a high level and also, easily to escape when refreshing. In a word, much SO2 before refreshing maybe good, because it shows the anti-micro procedure is reliable. But after refreshing, too much SO2 can cause unpleasant feeling, thus this kind of wine tend to have lower grades.

2.Relationship between acid and sugar

The ratio between acid and sugar may affect the quality. So I created a new factor and plot it. acid.sugar.ratio = total.acidity / residual sugar

But disappointedly, it doesn’t work as I expect. It comes to my mind that red wine are divided by the residual sugar, so I bucket the data and boxplot acidity and quality.

Dry: Dry wine’s residual sugar is under 4g/L. The sweetness is faint so the acidity didn’t affect the taste this much. But still, high level of acidity make the flavor rich and strong.
Semi-Dry: Semi-dry wine’s residual sugar is between 4-12g/L in which the acidity is very important. This plot strongley prove the saying: “Acidity is the skeleton of wine.” The wine has higher acidity tend to be better.
Semi-Sweet: Too less data to lead a result.

3. Relationship between chlorides and antimicrobial environment

The Chlorides itself is odorless, but under microbial action, it will transfer to Trichloroanisole(TCA). If the TCA is too much, the wine will have unpleasant smell like moldy old newspaper and wet cardboard. Here I create a factor that can measure the micro-growing environment. Sugar is consider to be positive to micro-growing, meanwhile alcohol and sulphates are negtive to micro-growing. The fomula is as following: micro.growing = residual.sugar / (alcohol * sulphates) Next I create the factor TCA.potential which is the product of micro.growing and chlorides. TCA.potential = micro.growing * chlorides Then I make a plot to figure out the relationship between TCA.potential and quality. Here I get a boxplot which shows TCA.potential is negtive to quality.

4. Other organic matter: Using density and alcohol to explore the other organic matter in the wine.

We know the density of red wine is less than water because of it contains alcohol and other organic matter. So I want to find the relationship between these organic matter and quality. First, I created a new factor names other.matter.density to measure the weight of wine removed alcohol and water. other.matter.density = density - 1000 * (alcohol/100*0.79 - (1 - alcohol/100*1)) The unit is g/dm^3.

The plot shows that the other.matter is negative to quality. The reason may be that the density of most great organic matter in wine(like acidity, tannin, etc.) has lower density than water, if these organic matter are higher, the wine is tend to have mellow taste.

多变量分析

探讨你在这部分探究中观察到的一些关系。通过观察感兴趣的特性，是否存在相互促进的特性？

free.sulfur.dioxide and total.sulfur.dioxide promote each other.

这些特性之间是否存在有趣或惊人的联系呢？

The factors which promote or inhibit the quality of wine have been explained in detail in the above.

选项：你是否创建过数据集的任何模型？讨论你模型的优缺点。

定稿图

1. Volatile acidity

We can see volatile acidity is negative to quality. But the best wine doesn’t have lowest volatile acidity. I guess there are 2 reasons: - The dataset of best quality wine are so small that causes the deviation. - The volatile acidity is not the only reason to judge the wine, so if the wine is excellent at other aspect but has acceptable high level volatile acidity, it still can be consider as high quality.

2. Citric acid

High quality wine has higher level of citric acid. Citric acid can add freshness and flavor in wine, which make the taste become rich.

3. Alcohol

High quality wine has higher level of alcohol. This may have following reasons: 1. High level of alcohol can protect the wine from microoraganism. 2. Wine which has high level of alcohol is more possible to be a good old wine.

4.Influence of SO2

We know that too much SO2 smell like rotten eggs, but too less SO2 will cause micro-polution. So in some degree, SO2 is indispensable. But what the difference between good and bad quality wine in this aspect? To explore this issue, I create 2 new factors:

SO2 ratio so2.ratio = free.sulfur.dioxide / Total Volatile Organic Compound = free.sulfur.dioxide / (free.sulfur.dioxide + volatile.acidity) SO2 ratio can measure the obvious degree of SO2.
SO2 control The sulphates control the so3+ in the wine, which can transform to so2. This factor can be consider as the release amount of SO2 when freshing the wine before taste. so2.control = (total.sulfur.dioxide - free.sulfur.dioxide) / sulphates

The plot shows us good wine have higher SO2 ratio and the slope of SO2 ratio and SO2 control is much large. The slope means the release rate SO2 when refreshing. From the plot, we can tell: - Good wine has higher SO2 ratio which can protect the wine from micro-polution better. - Good wine has higher SO2 releasing rate, which can much quickly make SO2 reach to a high level and also, easily to escape when refreshing. In a word, much SO2 before refreshing maybe good, because it shows the anti-micro procedure is reliable. But after refreshing, too much SO2 can cause unpleasant feeling, thus this kind of wine tend to have lower grades.

5.Relationship between acid and sugar

The ratio between acid and sugar may affect the quality. So I created a new factor and plot it. acid.sugar.ratio = total.acidity / residual sugar

But disappointedly, it doesn’t work as I expect. It comes to my mind that red wine are divided by the residual sugar, so I bucket the data and boxplot acidity and quality.

Dry: Dry wine’s residual sugar is under 4g/L. The sweetness is faint so the acidity didn’t affect the taste this much. But still, high level of acidity make the flavor rich and strong.
Semi-Dry: Semi-dry wine’s residual sugar is between 4-12g/L in which the acidity is very important. This plot strongley prove the saying: “Acidity is the skeleton of wine.” The wine has higher acidity tend to be better.
Semi-Sweet: Too less data to lead a result.

6. Relationship between chlorides and antimicrobial environment

The Chlorides itself is odorless, but under microbial action, it will transfer to Trichloroanisole(TCA). If the TCA is too much, the wine will have unpleasant smell like moldy old newspaper and wet cardboard. Here I create a factor that can measure the micro-growing environment. Sugar is consider to be positive to micro-growing, meanwhile alcohol and sulphates are negtive to micro-growing. The fomula is as following: micro.growing = residual.sugar / (alcohol * sulphates) Next I create the factor TCA.potential which is the product of micro.growing and chlorides. TCA.potential = micro.growing * chlorides Then I make a plot to figure out the relationship between TCA.potential and quality. Here I get a boxplot which shows TCA.potential is negtive to quality.

7. Other organic matter: Using density and alcohol to explore the other organic matter in the wine.

We know the density of red wine is less than water because of it contains alcohol and other organic matter. So I want to find the relationship between these organic matter and quality. First, I created a new factor names other.matter.density to measure the weight of wine removed alcohol and water. other.matter.density = density - 1000 * (alcohol/100*0.79 - (1 - alcohol/100*1)) The unit is g/dm^3.

The plot shows that the other.matter is negative to quality. The reason may be that the density of most great organic matter in wine(like acidity, tannin, etc.) has lower density than water, if these organic matter are higher, the wine is tend to have mellow taste.

反思

EDA not only need data processing technology, but also a very deep insight of the dataset. Just by this way can we get some interesting results.

为未来工作提供了至少一个提议或问题。

Construct more factors: Actually I am not very satisfied with the factor – ‘other matter’, we can construct this variable further. Maybe minus the residual sugar or the chlorides. And after know more about the red wine, we can find more factors that might be useful.
Reconstruct the factors: Because some factors are highly correlated which is bad for modelling. So we can use PCA or some other method to refine the factors.
Modelling: In my opnion, the quality of wine doesn’t depend on its advantages but its flaws since the balance of taste is the key value judging a wine. So maybe we can use the negative value to construct a model to deal predict a wine’s quality. In this way, we can know how the factors influence the quality in a more mathematical way.

解释了分析过程中所做的任何重要决定，以及这些决定对分析产生的影响。 When I create a new factor, I decided which original factors need to be used. And after trying, I get the rational results.

Reference

R语言对红酒各因素进行探索性分析

红葡萄酒质量探索分析

葡萄酒的骨架——酸度

入门：干型、半干、半甜和甜型葡萄酒有何区别？

你的葡萄酒Corked了吗？你喝过Corked葡萄酒吗？